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POWER BI DA-100 QUESTIONS WITH UPDATED ANSWERS
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POWER BI DA-100 QUESTIONS WITH UPDATEDANSWERS 2024 - 2025
What are the divisions of the core components of analytics? ANS - To analyze data, core components of
analytics are divided into the following categories:
-Descriptive
-Diagnostic
-Predictive
-Prescriptive
-Cognitive
What are descriptive analytics? ANS - Descriptive analytics help answer questions about what has
happened based on historical data. Descriptive analytics techniques summarize large datasets to
describe outcomes to stakeholders.
What are examples of descriptive analytics? ANS - An example of descriptive analytics is generating
reports to provide a view of an organization's sales and financial data.
What are diagnostic analytics? ANS - Diagnostic analytics help answer questions about why events
happened. Diagnostic analytics techniques supplement basic descriptive analytics, and they use the
findings from descriptive analytics to discover the cause of these events.
What are the steps of diagnostic analytics? ANS - Performance indicators are further investigated to
discover why these events improved or became worse. Generally, this process occurs in three steps:
1. Identify anomalies in the data. These anomalies might be unexpected changes in a metric or a
particular market.
2. Collect data that's related to these anomalies.
3. Use statistical techniques to discover relationships and trends that explain these anomalies.
,What are predictive analytics? ANS - Predictive analytics help answer questions about what will happen
in the future. Predictive analytics techniques use historical data to identify trends and determine if
they're likely to recur.
What techniques does predictive analytics use? ANS - Techniques include a variety of statistical and
machine learning techniques such as neural networks, decision trees, and regression.
What are prescriptive analytics? ANS - Prescriptive analytics help answer questions about which actions
should be taken to achieve a goal or target. By using insights from predictive analytics, organizations can
make data-driven decisions. This technique allows businesses to make informed decisions in the face of
uncertainty.
What tools does prescriptive analytics rely on? ANS - Prescriptive analytics techniques rely on machine
learning strategies to find patterns in large datasets.
What are cognitive analytics? ANS - Cognitive analytics attempt to draw inferences from existing data
and patterns, derive conclusions based on existing knowledge bases, and then add these findings back
into the knowledge base for future inferences, a self-learning feedback loop. Cognitive analytics help
you learn what might happen if circumstances change and determine how you might handle these
situations.
How are inferences structured for cognitive analytics? ANS - Inferences aren't structured queries based
on a rules database; rather, they're unstructured hypotheses that are gathered from several sources and
expressed with varying degrees of confidence. Effective cognitive analytics depend on machine learning
algorithms, and will use several natural language processing concepts to make sense of previously
untapped data sources, such as call center conversation logs and product reviews.
What are the different data roles? ANS - -Business analyst
-Data analyst
-Data engineer
-Data scientist
-Database administrator
, What is the role of the business analyst? ANS - While some similarities exist between a data analyst and
business analyst, the key differentiator between the two roles is what they do with data. A business
analyst is closer to the business and is a specialist in interpreting the data that comes from the
visualization.
What is the role of the data analyst? ANS - A data analyst enables businesses to maximize the value of
their data assets through visualization and reporting tools such as Microsoft Power BI. Data analysts are
responsible for profiling, cleaning, and transforming data. Their responsibilities also include designing
and building scalable and effective data models, and enabling and implementing the advanced analytics
capabilities into reports for analysis.
What are the responsibilities of the data analyst with respect to Power BI ANS - A data analyst is also
responsible for the management of Power BI assets, including reports, dashboards, workspaces, and the
underlying datasets that are used in the reports. They are tasked with implementing and configuring
proper security procedures, in conjunction with stakeholder requirements, to ensure the safekeeping of
all Power BI assets and their data.
How do data analyst interreact with the data engineer and database administrator? ANS - Data analysts
work with data engineers to determine and locate appropriate data sources that meet stakeholder
requirements. Additionally, data analysts work with the data engineer and database administrator to
ensure that the analyst has proper access to the needed data sources. The data analyst also works with
the data engineer to identify new processes or improve existing processes for collecting data for
analysis.
What is the role of the data engineer? ANS - Data engineers provision and set up data platform
technologies that are on-premises and in the cloud. They manage and secure the flow of structured and
unstructured data from multiple sources. The data platforms that they use can include relational
databases, nonrelational databases, data streams, and file stores. Data engineers also ensure that data
services securely and seamlessly integrate across data services.
Who does the data engineer work with? ANS - As a data analyst, you would work closely with a data
engineer in making sure that you can access the variety of structured and unstructured data sources
because they will support you in optimizing data models, which are typically served from a modern data
warehouse or data lake.
Who can become a data engineer? ANS - Both database administrators and business intelligence
professionals can transition to a data engineer role; they need to learn the tools and technology that are
used to process large amounts of data.
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